The use of simulation in the design of a road transport incident detection algorithm

Automatic incident detection is becoming one of the core tools of urban traffic management, enabling more rapid identification and response to traffic incidents and congestion. Existing traffic detection infrastructure within urban areas (often installed for traffic signal optimization) provides urban traffic control systems with a near continuous stream of data on the state of traffic within the network. The creation of a simulation to replicate such a data stream therefore provides a facility for the development of accurate congestion detection and warning algorithms. This paper describes firstly the augmentation of a commercial traffic model to provide an urban traffic control simulation platform and secondly the development of a new incident detection system (RAID-Remote Automatic Incident Detection), with the facility to use the simulation platform as an integral part of the design and calibration process. A brief description of a practical implementation of RAID is included along with summary evaluation results

Synergistic combination of systems for structural health monitoring and earthquake early warning for structural health prognosis and diagnosis

Earthquake early warning (EEW) systems are currently operating nationwide in Japan and are in beta-testing in California. Such a system detects an earthquake initiation using online signals from a seismic sensor network and broadcasts a warning of the predicted location and magnitude a few seconds to a minute or so before an earthquake hits a site. Such a system can be used synergistically with installed structural health monitoring (SHM) systems to enhance pre-event prognosis and post-event diagnosis of structural health. For pre-event prognosis, the EEW system information can be used to make probabilistic predictions of the anticipated damage to a structure using seismic loss estimation methodologies from performance-based earthquake engineering. These predictions can support decision-making regarding the activation of appropriate mitigation systems, such as stopping traffic from entering a bridge that has a predicted high probability of damage. Since the time between warning and arrival of the strong shaking is very short, probabilistic predictions must be rapidly calculated and the decision making automated for the mitigation actions. For post-event diagnosis, the SHM sensor data can be used in Bayesian updating of the probabilistic damage predictions with the EEW predictions as a prior. Appropriate Bayesian methods for SHM have been published. In this paper, we use pre-trained surrogate models (or emulators) based on machine learning methods to make fast damage and loss predictions that are then used in a cost-benefit decision framework for activation of a mitigation measure. A simple illustrative example of an infrastructure application is presented

Local Traffic Safety Analyzer – Improved Road Safety and Optimized Signal Control for Future Urban Intersections

Improving road safety and optimizing the traffic flow – these are major challenges at urban intersections. In particular, strengthening the needs of vulnerable road users (VRUs) such as pedestrians, cyclists and e-scooter drivers is becoming increasingly important, combined with support for automated and connected driving. In the LTSA project, a new system is being developed and implemented exactly for this purpose. The LTSA is an intelligent infrastructure system that records the movements of all road users in the vicinity of an intersection using a combination of several locally installed sensors e.g. video, radar, lidar. AI-based software processes the detected data, interprets the movement patterns of road users and continuously analyzes the current traffic situation (digital twin). Potentially dangerous situations are identified, e.g. right turning vehicles and simultaneously crossing VRUs, and warning messages can be sent to connected road users via vehicle-to-infrastructure communication (V2X). Automated vehicles can thus adapt their driving maneuvers. In addition, the collected data is applied to improve traffic light control depending on the current traffic situation, especially for VRUs. This abstract describes the LTSA system and its implementation in the German city of Potsdam. The current project state is presented and an outlook on next steps is given

Futuristic intelligent transportation system architecture for sustainable road transportation in developing countries

Published Conference ProceedingsSustainable road transportation has become a challenge particularly in the developing countries. Literature suggests that the ability of the transport system to respond to the mobility needs of people and goods is hampered by a continuous increase in traffic demand as a result of higher levels of urbanization, population growth, changes in population density and motorization. These factors result in traffic crashes, traffic congestion and consequent increase in travel times, fuel consumption and carbon emissions, which reduce the efficiency of mobility systems and make it unsustainable. Certain measures such as traffic control and management, congestion warning, road conditions warning, route guidance and use of eco- friendly and green vehicles are being considered to meet the challenges. Arguments have emerged that Intelligent Transportation Systems (ITS) are important to meet these challenges of achieving virtually traffic crash-free, clean and efficient mobility. This requires the development of an integrated communication architecture that provides a common frame for the road and traffic infrastructure, environment and vehicle systems to work together through Information Communication Technology (ICT) system. Therefore, this investigation explored the various ITS that are relevant to road transportation in the context of developing countries; examined the perception of road users on the use of ITS and its impacts on travel behavior; and developed a conceptual futuristic communication ITS architecture by integrating land use, road, traffic, human and environmental parameters with ICT for sustainable road transportation in developing countries. The study was conducted based on critical review of relevant literature and industrial innovations to examine the ITS system(s) applicable to developing countries. A survey was conducted in two cities of a developing country, India, to observe the perception of people, particularly road users on the use of ITS and its impacts on their travel. This was followed by development of a conceptual ITS architecture by integrating land use, activity, traffic, road infrastructure, vehicle, ICT, road user variable and indicators related to sustainable road transportation. Findings suggest that appropriate ITS with the use of ICT, can provide acceptable effective real time information regarding the road and traffic conditions, which will enable the road users in their journey planning, to avoid unwarranted incidents and moreover enhance safe and efficient mobility in the roads of developing countries

Synergizing Roadway Infrastructure Investment with Digital Infrastructure for Infrastructure-Based Connected Vehicle Applications: Review of Current Status and Future Directions

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.The safety, mobility, environmental and economic benefits of Connected and Autonomous Vehicles (CAVs) are potentially dramatic. However, realization of these benefits largely hinges on the timely upgrading of the existing transportation system. CAVs must be enabled to send and receive data to and from other vehicles and drivers (V2V communication) and to and from infrastructure (V2I communication). Further, infrastructure and the transportation agencies that manage it must be able to collect, process, distribute and archive these data quickly, reliably, and securely. This paper focuses on current digital roadway infrastructure initiatives and highlights the importance of including digital infrastructure investment alongside more traditional infrastructure investment to keep up with the auto industry's push towards this real time communication and data processing capability. Agencies responsible for transportation infrastructure construction and management must collaborate, establishing national and international platforms to guide the planning, deployment and management of digital infrastructure in their jurisdictions. This will help create standardized interoperable national and international systems so that CAV technology is not deployed in a haphazard and uncoordinated manner

Hardware-in-the-Loop and Road Testing of RLVW and GLOSA Connected Vehicle Applications

This paper presents an evaluation of two different Vehicle to Infrastructure (V2I) applications, namely Red Light Violation Warning (RLVW) and Green Light Optimized Speed Advisory (GLOSA). The evaluation method is to first develop and use Hardware-in-the-Loop (HIL) simulator testing, followed by extension of the HIL testing to road testing using an experimental connected vehicle. The HIL simulator used in the testing is a state-of-the-art simulator that consists of the same hardware like the road side unit and traffic cabinet as is used in real intersections and allows testing of numerous different traffic and intersection geometry and timing scenarios realistically. First, the RLVW V2I algorithm is tested in the HIL simulator and then implemented in an On-Board-Unit (OBU) in our experimental vehicle and tested at real world intersections. This same approach of HIL testing followed by testing in real intersections using our experimental vehicle is later extended to the GLOSA application. The GLOSA application that is tested in this paper has both an optimal speed advisory for passing at the green light and also includes a red light violation warning system. The paper presents the HIL and experimental vehicle evaluation systems, information about RLVW and GLOSA and HIL simulation and road testing results and their interpretations

Design, Specification, Implementation and Evaluation of a Real-Time Queue Warning System

University of Minnesota M.S. thesis. December 2017. Major: Civil Engineering. Advisor: John Hourdos. 1 computer file (PDF); viii, 72 pages.The formation and propagation of queues on urban freeways is an unavoidable result of the ever-increasing traffic demand. Traffic queues increase on-road congestions and reduce roadway network efficiency. More importantly, some of these queues can cause serious rear-end collisions, resulting in property damages and injuries. This thesis presents the design, specification, implementation and evaluation of an infrastructure based Queue Warning system (QWarn) that is capable of detecting dangerous traffic conditions, i.e. crash-prone conditions, on freeways and delivering warning messages to drivers, in order to increase their alertness and ultimately reduce the frequency of crashes. This effort approaches the topic from the quantification of traffic flow to the multi-layer system design along with different methodologies including the traffic assessment modeling and the development of control algorithms. This study utilizes measurements of individual vehicle speeds and time headways at two fixed locations on the freeway mainline, as the major type of data for the system’s operation. This thesis focuses on a case study and evaluation of the proposed system implemented on a high crash frequency freeway section. The Queue Warning system was implemented at the right lane of a 1.7-mile-long freeway segment of Interstate 94 Westbound near downtown Minneapolis where the event frequency prior to the systems installation was 212.25 conflict events per million vehicles traveled. Machine Vision Detectors (MVD) are installed on a nearby rooftop capturing the Real-Time vehicle data. The data were delivered over the Minnesota Traffic Observatory’s (MTO) communication network to a server running the main control algorithm. The control algorithm assesses the dangerousness of the given traffic condition and responds with a warning result based on a multi-metrics traffic evaluation model and complex control reasoning that ensures consistency and accuracy. The system translates the warning result into readable messages and delivers them to the two sets of signs located upstream of the detection zone. A three-month investigation of the operations of the QWarn system shown a reduction in conflict event frequency to 135.79 per million vehicle traveled. In conclusion, this thesis proposed the framework as well as details of a Queue Warning system is also evaluated the methodology by implementing a working prototype that delivers warning messages to road users on an urban freeway segment. The result shows a decrease of conflict event frequency and proves the feasibility of the proposed methodology

Work domain analysis and intelligent transport systems: Implications for vehicle design

This article presents a Work Domain Analysis (WDA) of the road transport system in Victoria, Australia. A series of driver information requirements and tasks that could potentially be supported through the use of Intelligent Transport Systems (ITS) are then extracted from the WDA. The potential use of ITS technologies to circumvent these information gaps and provide additional support to drivers is discussed. It is concluded that driver information requirements are currently not entirely satisfied by contemporary vehicle design and also that there are a number of driving tasks that could be further supported through the provision of supplementary systems within vehicles